Quantifying the material and structural determinants of bone strength

3
Quantifying the material and structural determinants
of bone strength
Mary L. Bouxsein, PhD a, *, Ego Seeman, MD b
a Assistant Professor of Orthopaedic Surgery, Orthopedic Biomechanics Laboratory, Beth Israel Deaconess Medical Center and
Department of Orthopaedic Surgery, Harvard Medical School, RN115, 330 Brookline Ave, Boston, MA 02215, USA
b Professor of Medicine, Austin Health, University of Melbourne, Melbourne, Australia
Keywords:
bone strength
bone quality
microarchitecture
quantitative computed tomography
magnetic resonance imaging
finite element analysis
Best Practice & Research Clinical Rheumatology 23 (2009) 741–753
Contents lists available at ScienceDirect
Best Practice & Research Clinical
Rheumatology
journal homepage: www.elsevierhealth.com/berh
The ability of a bone to resist fracture depends on the amount of
bone present, the spatial distribution of the bone mass as cortical
and trabecular bone and the intrinsic properties of the bone
material. Whereas low areal bone mineral density (aBMD) predicts
fractures, its sensitivity and specificity is low, as over 50% of fractures
occur in persons without osteoporosis by BMD testing and
most women with osteoporosis do not sustain a fracture. New
non-invasive imaging techniques, including three-dimensional
(3D) assessments of bone density and geometry, microarchitecture
and integrated measurements of bone strength such as finite
element analysis (FEA), provide estimates of bone strength that
can be used to increase the sensitivity and specificity of fracture
risk assessment. Initial observations have shown that these techniques
provide information that will improve our understanding of
the pathophysiology of skeletal fragility and suggest that these
techniques are likely to have a role in the clinical management of
individuals at risk for fracture.
Ó 2009 Elsevier Ltd. All rights reserved.
Fractures due to osteoporosis are common, with one in three women and one in five men over age
50 predicted to suffer a fracture in their lifetime [1]. As the proportion of elderly in the population is
growing exponentially, the number of fractures is expected to double or triple in the next 50 years.
While drug therapy is efficacious in reducing the risk of vertebral fracture, many challenges remain as
few drugs have been shown to reduce the risk of non-vertebral fractures, and usually this risk reduction
* Corresponding author. Tel.: þ1 617 667 2940; Fax: þ1 617 667 7175.
E-mail address: mbouxsei@bidmc.harvard.edu (M.L. Bouxsein).
1521-6942/$ – see front matter Ó 2009 Elsevier Ltd. All rights reserved.
doi:10.1016/j.berh.2009.09.008

742
is no more that 20%, and around 40–59% for hip fractures. Moreover, no drugs have been shown to
reduce the risk of hip fractures in women or men over 75 years of age [2]. In addition, access to and
compliance with osteoporosis therapies are poor [3].
Osteoporosis is defined as ‘‘a disease characterized by low bone mass and microarchitectural
deterioration of bone tissue, leading to enhanced bone fragility and a consequent increase in fracture
risk.’’[4] A fracture occurs when the external force applied to a bone exceeds its strength. For a given
loading condition, the ability of a bone to resist fracture depends on the amount of bone, the spatial
distribution of the bone mass and the intrinsic properties of the materials that comprise the bone [5].
Presently, diagnosis of osteoporosis is based on measurement of areal bone mineral density (aBMD)
by dual-energy X-ray absorptiometry (DXA). While aBMD is a predictor of fracture risk [6], it lacks
sensitivity and specificity; most women with osteoporosis do not sustain a fracture and over 50% of
women who sustain a fracture do not have osteoporosis [7–9]. Moreover, changes in BMD following
therapy explain only 4–30% of the fracture risk reduction [10–13].
These observations have focussed attention on other factors that influence bone strength [14,15]
and have motivated development of new technologies to assess these factors. In this review, the
general considerations for the non-invasive assessment of the material and structural determinants of
bone strength are presented and developments in this area are critically reviewed. The focus of
attention here is on technologies that can be applied clinically.
Criteria for evaluating new technologies
Imaging technologies must be accurate and precise and must have established quality control
procedures, standardised data acquisition and analysis, as well as methods for cross-calibration of
devices at different clinical centres [16]. Data that help define the clinical utility of a new imaging
technique include: (1) sex- and age-specific reference data; (2) assessment of disease severity; (3)
associations with fracture risk in untreated subjects; and (4) changes in the measurement with
worsening of the disease or with therapeutic intervention. Ultimately, imaging techniques must have
clinical utility d they must identify individuals at risk for fracture with high sensitivity, assist in
monitoring of therapy and provide potential surrogates for anti-fracture efficacy.
The techniques should also provide insights into the pathogenesis of disease. This is a particularly
important concern because some techniques rely on models which simplify the structure of bone. As
such these simplifications may produce misleading notions regarding the pathogenesis of disease and
the effects of treatment. There are many examples of this, and these limitations are discussed in this
article.
Imaging Techniques
M.L. Bouxsein, E. Seeman / Best Practice & Research Clinical Rheumatology 23 (2009) 741–753
Dual-energy X-ray absorptiometry (DXA) and aBMD
Introduced about 25 years ago, dual-energy X-ray absorptiometry (DXA) provides a quantitative
assessment of mineralised bone mass at the axial and appendicular skeleton in vivo. This technique
measures the attenuation of photons of two different energies during radiation transmission. Bone
mineral content (BMC, g) and aBMD (g cm –2 ) of a region of interest are obtained. As low aBMD is
a strong risk factor for fractures [17], this technique provided the basis for the World Health Organization
(WHO)’s guidelines for diagnosis of osteoporosis [18]. Advantages to DXA include a low radiation
exposure, excellent precision, low cost, ease of use and short measurement times. However, the
measurements are two-dimensional (2D) so larger bones may have higher aBMD than smaller bones
because of differences in size [19]; the bone with the lower BMD may not have gained less or lost more
bone. DXA also does not distinguish cortical and cancellous bone. Nor do changes in aBMD provide
information regarding the morphological basis of that change; aBMD may decrease more in one person
than another because resorption from the endosteal envelope is greater and/or periosteal apposition is
less. Bone loss may occur mainly from trabecular bone or from the intracortical or endocortical surfaces
or from both. DXA cannot assess 3D geometry or trabecular architecture. Furthermore, measurements
are subject to artefacts due to degenerative changes such as osteophytes and aortic calcification. Thus,

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although DXA is currently the gold standard for clinical assessment of fracture risk, its shortcomings
are increasingly being recognised.
DXA in the assessment of bone structure d hip structural analysis (HSA)
Bone geometry, an important determinant of bone strength, has been assessed non-invasively by
several methods including radiogrammetry, automated DXA-based analysis of X-ray attenuation
profiles (termed ‘hip structural analysis’, HSA) and 3D imaging methods such as computed tomography
or magnetic resonance imaging.
HSA has been widely used because structural properties can be estimated from routine DXA scans, and
the software needed to compute these variables is now provided by several of the DXA manufacturers.
HSA uses data from 2D DXA scans to derive measurements of bone geometry at the proximal femur,
including the amount and distribution of bone mass, bone morphology and indices of bone strength such
as section modulus (an index of resistance to bending), buckling ratio and bone area (an index of
resistance to compression) [20]. However, some of these indices are derived under the assumption that
the bone cross section is circular at the femoral neck and shaft, and elliptical at the inter-trochanteric
region, that the tissue mineral density is constant and that cortical and trabecular bone in the cross
section are a constant proportion [21]. Moreover, the method is limited to analyses of a single plane.
HSA has been used to examine effects of anti-resorptive and anabolic therapies on femoral
geometry [21–25]. However, anti-resorptive therapies increase tissue mineral density [26–29],
whereas teriparatide may decrease it [30]. An increase in the amount of mineral per unit bone volume
is ‘seen’ by HSA as an increase in the cross-sectional area of bone material, leading an investigator to
infer that there has either been periosteal apposition and/or endocortical apposition produced by
antiresorptive agents; effects that are not produced by this class of drug. Thus, interpretation of HSA
from studies where mineralisation density changes is difficult and suspect.
Several studies have used this method to provide information regarding age-, race- and sex-related
differences in femoral geometry that may contribute to hip fracture risk [31–39]; effects of physical
activity and hormone status on femoral geometry [40,41]; and genetic determinants of femoral
structure [42–44]. Because some of the assumptions underlying HSA have not been tested across ages
and populations, conclusions from these studies should be viewed with caution.
Several prospective studies report that HSA-derived measures of femoral geometry are associated
with risk of hip fracture [45–48]. However, it is unclear whether HSA provides information about
fracture risk that is independent of BMD. This is likely because femoral BMD and HSA-derived structural
properties are highly correlated because the same attenuation profile is used to compute the
measurements. Thus, conclusions regarding independent contributions of bone density and geometry
to femoral fragility are problematic using HSA.
We do not recommend the use of this technique because of the uncertainties and the potentially
misleading notions of bone physiology that can arise if the results are accepted on face value. Moreover,
other options are available for directly measuring the 3D geometry, such as magnetic resonance
imaging (MRI), computed tomography (CT) and high-resolution peripheral quantitative computed
tomography (HR-pQCT). These are being used in clinical studies to identify the relationships between
geometry, bone density and fracture risk.
Quantitative computed tomography (QCT)
In QCT, the X-ray source and detector rotate in synchronised fashion around the subject. Algorithms
are used to reconstruct the attenuation data into 3D images. Use of a bone mineral (or hydroxyapatite)
phantom allows calibration of the data, providing a measurement of bone density that is independent
of bone size. The cortical and trabecular compartments are measured separately (Fig. 1). QCT-based
bone measurements have been used to evaluate sex-, age- and ethnic-related differences in vertebral
and femoral geometry and density, providing insights into the development of skeletal fragility [49–
52]. As the variance in measures of vBMD by QCT are greater than by using DXA, particularly for
cancellous bone, changes expressed in percentage terms are greater than changes observed by DXA.
Accelerated decrease in trabecular bone is observed with greater decreases in women than men in

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Fig. 1. Quantitative computed tomography image of the lumbar spine, showing bone density phantom, and distinct analysis of
cortical and trabecluar bone compartments. Images courtesy of Dr. Thomas Lang, UCSF.
midlife [49]. Effects of drug therapy on cancellous and cortical bone have been documented using QCT
[53–58]. There are many cross-sectional studies showing an association between QCT bone density and
fracture risk [59–68] but there is no consensus on whether QCT performs better than DXA in terms of
predicting fracture risk. One prospective study of risk of hip fracture in men used QCT to show that
bone density and morphology of the femoral neck were independent predictors of hip fracture [69].
Standard QCT generates images with in-plane voxel sizes of 300–500 mm and slice thickness of
1–3 mm and are therefore not adequate to assess trabecular bone microarchitecture, as trabecular
thickness ranges from approximately 100 to 300 mm. High-resolution imaging with multislice spiral CT
scanners (HRCTs) has been used to assess vertebral trabecular architecture (Fig. 2), achieving images
with in-plane voxel size of 150–180 mm and slice thickness of 300–500 mm [70,71]. HRCT provides
superior discrimination of vertebral fracture patients compared with BMD [70]. In monitoring changes
in vertebral trabecular architecture following 1 year of teriparatide therapy, HRCT provided complementary
information to that derived from densitometry [71].
Advantages to QCT are that it can be employed on standard clinical scanners with relatively short
imaging times, providing robust assessment of geometry and volumetric bone density in trabecular
and cortical compartments at sites most prone to fracture, although even the low radiation exposure is
a concern to some. To define the clinical utility of this technique, additional data are needed on the
ability of QCT-based measures to predict fracture risk prospectively and to monitor anti-fracture
efficacy of drug interventions.
High-resolution peripheral computed tomography (HR-pQCT)
HR-pQCT measures bone density and trabecular and cortical microarchitecture, the distal radius
and distal tibia with isotropic voxel size of w80 mm [72–80] (Fig. 3). This technique has excellent
precision for both density (

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Fig. 2. Multi-slice, high-resolution computed tomography images of the 12th thoracic vertebrae, showing image acquisition,
identification of the region of interest, and segmentation of the vertebral trabecular bone. Images courtesy of Dr. Claus Glüer,
University of Kiel.
parameters measured by HR-pQCT in a standard patient analysis, including bone volume ratio,
trabecular number, derived trabecular thickness, derived trabecular separation and cortical thickness,
correlated well with measurements made with high-resolution micro-CT (i.e., 20-mm voxel size) [81].
Longitudinal HR-pQCT measurements indicate that whereas substantial cortical bone loss begins in
middle life in women, it begins mainly after age 75 in men [78]. By contrast, trabecular bone loss begins
early in adulthood in both women and men, such that approximately 40% of total life time trabecular
bone loss occurs before age 50, as compared withe less than 15% for cortical bone.
Cross-sectional studies have reported that microarchitecture measurements at the distal radius by
HR-pQCT discriminate postmenopausal women with a history of fragility fracture from those who have
not suffered a fracture, partly independent of BMD [72,75–77,82]. Preliminary reports have shown
treatment-related changes in bone architecture as assessed by HR-pQCT, including increased cortical
thickness following 1 year of denosumab [83] or strontium ranelate [84] therapy. As denosumab likely
increases tissue mineral density due to its profound suppression of bone resorption [85] and strontium
Fig. 3. High-resolution peripheral quantitative computed tomography image (voxel size ¼ 82 mm 3 ) of the distal radius (left) and
distal tibia (right). Trabecular bone appears white, on a dark background.

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ranelate is incorporated into the mineral substance of bone [86], it is not known whether these
observations are true changes in bone morphology or artefacts due to altered edge-detection and/or
partial volume effects.
Altogether, HR-pQCT is promising for assessment of trabecular and cortical architecture in vivo with
high precision. The disadvantages are that it requires specialised scanners, and measurements are
limited to peripheral skeletal sites. Furthermore, motion artefacts are common, requiring re-scanning
of many patients.
Magnetic resonance imaging (MRI)
Magnetic resonance (MR) imaging is a non-ionising method that uses a strong magnetic field in
combination with specialised sequences of radio-frequency pulses to generate 3D images of bone
structure [87]. Because free hydrogen in water provides the ‘signal’ in this type of MR imaging and
since the water content of bone is minimal, there is generally little signal provided by bone in
standard MR imaging. As a result, the bone structure is assessed indirectly via measurements of
the surrounding marrow and other soft tissues (Fig. 4). Advances in the past decade have focussed
on image acquisition and analysis techniques to overcome inherent obstacles in MR imaging of
bone [88].
High-resolution MR imaging is performed at peripheral skeletal sites (e.g., distal radius, distal tibia
and calcaneus) using clinical MR scanners combined with specially designed coils. In vivo resolutions of
150–300 mm in plane and a slice thickness of 300–500 mm have been achieved [89,90]. With this
resolution, it is not possible to produce accurate values for most features of trabecular architecture.
Nonetheless, the ‘apparent’ trabecular properties that are derived from these images correlate with
trabecular architecture obtained with higher-resolution techniques [91,92]. Until recently, evaluation
of trabecular bone morphology was limited to appendicular sites. However, innovative surface coils
and pulse sequences show potential for MR-based assessments of trabecular structure in the proximal
femur [93–95] (Fig. 5).
MR-derived trabecular microarchitecture measurements reflect age- and disease-specific differences
[96,97], and differentiate patients with hip and vertebral fractures from controls with the best
performance achieved by combinations of structural parameters and BMD [98–103]. There are no
studies demonstrating prospective fracture risk prediction, and there are limited data on treatmentrelated
changes [104,105].
Fig. 4. Magnetic resonance image of the distal tibia (voxel size: 156 156 500 mm). Trabecular bone appears dark on a light
background of marrow. Image courtesy of Dr. Sharmila Majumdar, UCSF.

M.L. Bouxsein, E. Seeman / Best Practice & Research Clinical Rheumatology 23 (2009) 741–753 747
Fig. 5. Magnetic resonance image of the proximal femur. Image courtesy of Dr. Sharmila Majumdar, UCSF.
There are currently no non-invasive techniques available for clinical use that assess bone matrix
properties, such as the degree of mineralisation, collagen content and/or the degree of collagen crosslinking.
Yet, one particularly novel aspect of MRI is that it may allow non-invasive assessment of bone
matrix properties in addition to bone structure. Solid-state MR imaging uses the resonant signals of the
phosphorus ( [31] P) constituent of the bone mineral phase to determine the mineral content of bone
[106–110]. Bone tissue mineral density measurements acquired through [31] P solid-state MR
discriminate osteoporotic and osteomalacic animal models better than X-ray-based imaging methods
[108]. Wu and colleagues[109] report that combined 31 P and 1 H water- and fat-suppressed solid-state
imaging give MRI the unique ability to assess the organic and inorganic solid-phase densities of bone,
as well as the solid bone matrix density (organic þ inorganic). Although 31 P solid-state MRI has been
implemented in vivo with human subjects on a clinical 1.5 T system [111], solid-state MRI is still
a research tool. Solid-state imaging may become an excellent tool for longitudinal bone tissue density
evaluations (without consequence of radiation exposure), but currently, this method requires excessively
long imaging times (w1 h or more), most studies have used non-clinical scanners with strong
magnetic fields (4.7 T or greater) and custom-made coils. Thus, MRI is a non-ionising method that
allows 3D assessment of cortical and trabecular bone structure. Image data can be acquired in any
arbitrary axis with acquisition times of 10–15 min [88].
Finite element analysis (FEA) based on QCT- or hr-pQCT images
The finite element (FE) method was first applied to structural analysis in the 1950s, and it has since
been widely used in nearly every engineering and engineering-related field. In solid and structural
mechanics (bone mechanics included), it is the method of choice for evaluating the how a structure
with complex geometrical shape and heterogeneous distribution of material properties (e.g., a whole
bone) behaves when subjected to external loads.
The finite element approach begins by representing the object as a collection of building blocks, or
elements, each of which is defined by reference points, or nodes. The FE method can provide ‘estimates’
of quantities that are commonly obtained through mechanical testing (e.g., whole bone stiffness and
failure load), as well as quantities that are difficult, if not impossible, to measure experimentally
(e.g., strain distribution). However, the ability of the finite element solution to approximate the actual
biomechanical phenomenon depends on the quality of the input. For example, the choice of material

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properties and loading conditions influence the strength predictions. Nonetheless, this state-of-the-art
technique is among the most promising tools available today for clinical assessment of bone strength
and fracture risk [112].
3D-QCT (or HR-pQCT) scans are directly converted, voxel by voxel, into a finite element model,
which accurately represents the 3D geometry and heterogeneous density distribution of the bone of
interest (Fig. 6). Forces simulating activities that cause fractures are applied to this model, and the
stiffness and strength of the bone in response to the applied forces are computed. These analyses can
incorporate different in vivo loading conditions, such as compressive and bending loading for the
vertebrae, or stance and fall loading for the femur. Several studies in human cadaveric femurs,
vertebrae and forearms have shown that bone strength is better predicted by FE analyses than by BMD
alone [113–116].
Over 15 years ago, Faulkner and colleagues reported that QCT-based FE analysis of vertebral
strength discriminated between women with and without vertebral fracture, with less overlap
between the two groups than observed using QCT [117]. More recently, QCT-based FE analyses have
been shown to discriminate women with vertebral fractures from controls[118] and to explore the
mechanisms underlying increased bone strength following anabolic and/or anti-catabolic treatment[57,119,120,121].
The deleterious effects of glucocorticoids on femoral strength have also been
explored by in vivo QCT-based FE analyses [122]. In postmenopausal women matched for age, weight
and history of hormone therapy, FE analyses showed that femoral strength in women with a history of
glucocorticoid use was w15% lower than controls for both fall-loading and stance configurations.
The feasibility of in vivo micro-FEA using both MR and HR-pQCT has also been demonstrated in
clinical studies [78,82,123,124]. High-resolution MR images of trabecular bone in the distal radius were
subjected to FE analysis to determine effects of trabecular microarchitecture on bone mechanical
properties in normal and osteopenic postmenopausal women [123]. MR images of trabecular architecture
in the calcaneus were also assessed using FE to quantify the response to 1 year idoxifene [124].
In both cases, the use of FE analysis provided additional information regarding bone structure and
strength to that available from structure measurements alone. Thus, this approach warrants further
investigation. However, because this technique presently requires extensive computational resources
and specialised software, widespread evaluation will likely be limited. To date, there are few data on
the precision of the technique and its ability to reflect disease- and age-related changes, and no
prospective fracture studies exist. However, cross-sectional studies using HR-pQCT have shown the
FEA-based strength estimates discriminate women with prior history of distal radius fracture [76,82].
Improved imaging and computational methods have made subject-specific FE analyses more feasible,
and further technological advances will continue.
Fig. 6. Finite element model of the proximal femur in a sideways fall configuration. Colors represent plastic strain, showing likely
regions of failure. Image courtesy of Dr. David Kopperdahl, O.N. Diagnostics.

Conclusions
Novel non-invasive techniques for assessment of the structural determinants of bone strength are
available. These techniques quantify the macro- and microstructure of bone such as bone size, shape,
cortical thickness, cortical density, a surrogate of cortical porosity, trabecular number, thickness and
separation. FE analysis, by combining bone geometry with material characteristics, provides good
estimates of whole bone strength. Whether these strength and/or morphological features singly or
together will improve fracture prediction or serve as surrogates of anti-fracture efficacy is not known.
Although several studies provide promising data for these technique, these methodologies remain
research tools as most have not been rigorously tested for their ability to predict fracture risk in
prospective studies and to monitor treatment response. Use of 3D imaging modalities to assess the
determinants of bone strength is a research area of high interest and relevance to clinicians. However,
there is a need for additional developments and studies to determine the clinical utility of these
imaging modalities. Future research is aimed at developing techniques that are better suited to assess
those at highest risk of fracture, to diagnose patients early in the disease process, to identify specific
treatable components of skeletal fragility and to monitor treatment efficacy. These developments are
needed given the inevitable future of a growing elderly population combined with shrinking resources
for medical care.
Acknowledgements
We thank Drs. Sharmala Majumdar, Claus Glüer, Thomas Lang and David Kopperdahl for generously
providing images.
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